{"title":"评估技术债务的规模、成本和类型","authors":"B. Curtis, Jay Sappidi, Alexandra Szynkarski","doi":"10.1109/MTD.2012.6226000","DOIUrl":null,"url":null,"abstract":"This study summarizes results of a study of Technical Debt across 745 business applications comprising 365 million lines of code collected from 160 companies in 10 industry segments. These applications were submitted to a static analysis that evaluates quality within and across application layers that may be coded in different languages. The analysis consists of evaluating the application against a repository of over 1200 rules of good architectural and coding practice. A formula for estimating Technical Debt with adjustable parameters is presented. Results are presented for Technical Debt across the entire sample as well as for different programming languages and quality factors.","PeriodicalId":156499,"journal":{"name":"2012 Third International Workshop on Managing Technical Debt (MTD)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"99","resultStr":"{\"title\":\"Estimating the size, cost, and types of Technical Debt\",\"authors\":\"B. Curtis, Jay Sappidi, Alexandra Szynkarski\",\"doi\":\"10.1109/MTD.2012.6226000\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study summarizes results of a study of Technical Debt across 745 business applications comprising 365 million lines of code collected from 160 companies in 10 industry segments. These applications were submitted to a static analysis that evaluates quality within and across application layers that may be coded in different languages. The analysis consists of evaluating the application against a repository of over 1200 rules of good architectural and coding practice. A formula for estimating Technical Debt with adjustable parameters is presented. Results are presented for Technical Debt across the entire sample as well as for different programming languages and quality factors.\",\"PeriodicalId\":156499,\"journal\":{\"name\":\"2012 Third International Workshop on Managing Technical Debt (MTD)\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-06-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"99\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 Third International Workshop on Managing Technical Debt (MTD)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MTD.2012.6226000\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Third International Workshop on Managing Technical Debt (MTD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MTD.2012.6226000","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Estimating the size, cost, and types of Technical Debt
This study summarizes results of a study of Technical Debt across 745 business applications comprising 365 million lines of code collected from 160 companies in 10 industry segments. These applications were submitted to a static analysis that evaluates quality within and across application layers that may be coded in different languages. The analysis consists of evaluating the application against a repository of over 1200 rules of good architectural and coding practice. A formula for estimating Technical Debt with adjustable parameters is presented. Results are presented for Technical Debt across the entire sample as well as for different programming languages and quality factors.
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